Human Capital Policy and Inequality: 1 of 5

“Most of the family income gap in enrollment is due to long-term factors that produce abilities needed to benefit from participating in college”(Heckman p. 97)

We shall continue the discussion of Professor Carneiro’s and Heckman’s essay, “Human Capital Policy” and its recommendations for human capital policies. This section is primarily devoted to citing empirical evidence that de-emphasizes our preoccupation with short-term, adolescent-age credit constraints in determining an individual’s class destination. They do not as much exclude the short-term credit constraint explanation as much as propose an alternative that envelops it and provides greater explanatory power. The authors argue, quite well, that a family’s income over the child’s lifespan, particularly in her early years, is more formative due to the “inability of the child to buy the parental environment…that [forms] the cognitive and noncognitive abilities required for success in school”(Heckman p. 97). If we look at a family’s income over the child’s pre-college life, wealthier families are less likely to experience credit constraints in the child’s adolescent year, and; thus, short-term credit constraint serves as a proxy for long-term family income. Because of this confounding effect, prior studies finding correlation between credit constraint and educational attainment assumed it as an explanatory variable for educational attainment discrepancies. Similarly, most of these studies do not differentiate between the effects of rising tuition costs and availability of credit.

To correct this, Professor Heckman incorporates the family’s permanent income into the model to examine its role and then asks how much more can credit constraint explain. The professors perform their modeling and analysis on college enrollment and completion. Using Current Population Survey data, they find the main explanatory variable to be long-term income and family environment, whereas credit constraint plays only minor role in accounting for variability in college-enrollment. When they instead use NLSY79 data to examine other forms of college-participation, such as college completion or college quality, they see that credit constrains do not surface for white males and are most significant for Hispanic individuals, though still only in a small amount.

To strengthen their argument for investing in earlier childhood rather than education, they address and counter one of Alan Kruegman’s assertions that returns to education are higher for low-income students than high-income students. All empirical evidence suggests that high income students reap greater benefits. Furthermore, these studies may underestimate the increased benefits because they do not account for school quality. Overall, empirical evidence indicates that the family’s permanent income is the primary determinant in a child’s educational and income outcomes.

They conclude that “there is scope for intervention to alleviate short-term constraints, but one should not expect to reduce the enrollment gaps…substantially” (Heckman p. 99) through these interventions. This is because by the time the child finishes high school, “family factors present from birth through adolescence” almost wholly determine her cognitive and non-cognitive ability leaving little leverage for policies that aim to reverse or mitigate deficiencies in readiness. As a result, interventions should consist of targeted policies that aim to alleviate income and opportunity differentials in early childhood.

A major shortfall observed in their analysis is the absence of non-male genders, which pose the question whether the patterns found herein hold for women and others as well.